CN114565325A - Big data analysis method and system of power Internet of things - Google Patents

Big data analysis method and system of power Internet of things Download PDF

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CN114565325A
CN114565325A CN202210455199.1A CN202210455199A CN114565325A CN 114565325 A CN114565325 A CN 114565325A CN 202210455199 A CN202210455199 A CN 202210455199A CN 114565325 A CN114565325 A CN 114565325A
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CN114565325B (en
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陆兴
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Ruizhi Technology Group Co ltd
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Abstract

The application relates to the field of digital processing, in particular to a big data analysis method and a big data analysis system for an electric power Internet of things, wherein all common nodes in an Internet of things unit send generated original electric power data to computing nodes in the Internet of things unit to which the common nodes belong; the computing node computes characteristic power data of the Internet of things unit to which the computing node belongs according to the received original power data; the computing node stores the obtained characteristic power data and original power data of the Internet of things unit to the cloud as a storage unit; the cloud receives an access request of a user, obtains characteristic power data or original power data according to the access request query, and analyzes the characteristic power data or the original power data to obtain an access result; and the cloud end returns the access result to the user as the response of the access request. According to the method and the device, the electric power data stored in the cloud can be rapidly inquired and analyzed, and the performance of the cloud is improved.

Description

Big data analysis method and system of power Internet of things
Technical Field
The application relates to the field of digital processing, in particular to a big data analysis method and a big data analysis system for an electric power internet of things.
Background
With the construction and implementation of a power physical network, the requirements of the power industry on informatization and intellectualization are increasingly raised, power data generated in a power internet of things system are increased explosively, and in order to store massive power data, the power industry usually deploys the power data at the cloud at present.
However, there are different kinds of power systems in the power internet of things system, such as: production regulation and operation system, marketing and operation service system, user's action perception system, asset life cycle management system etc. have different power equipment again in the electric power system of difference, for example: the production regulation and control and operation system is provided with an online sensor, a networked measuring device and the like, the marketing and operation service system is provided with power consumption data acquisition equipment, EV charging operation equipment and the like, the user behavior sensing system is provided with random computing equipment and the like, the asset life cycle management system is provided with online detection equipment and the like, and different power equipment generates different power data and has different purposes.
Massive different types of electric power data are stored in the cloud, and when the electric power data are called by the cloud for analysis, more time is usually consumed for query and more time is also consumed for analysis, so that the performance of the cloud is influenced.
Therefore, how to quickly query and analyze the power data stored in the cloud to improve the performance of the cloud is a technical problem that needs to be solved by those skilled in the art.
Disclosure of Invention
The application provides a big data analysis method and a big data analysis system of an electric power internet of things, so that electric power data stored in a cloud can be rapidly inquired and analyzed, and the performance of the cloud is improved.
In order to solve the technical problem, the application provides the following technical scheme:
s110, all common nodes in an Internet of things unit send generated original electric power data to a computing node in the Internet of things unit to which the common nodes belong; step S120, calculating by the computing node according to the received original power data to obtain characteristic power data of the Internet of things unit to which the computing node belongs; step S130, the computing node stores the obtained characteristic power data and original power data of the Internet of things unit to the cloud as a storage unit; step S140, the cloud receives an access request of a user, obtains characteristic power data or original power data according to the access request query, and analyzes the characteristic power data or the original power data to obtain an access result; and step S150, the cloud end takes the access result as a response of the access request and returns the access result to the user.
The big data analysis method of the power internet of things is preferably used for timing the time period
Figure 44537DEST_PATH_IMAGE001
After starting, the Internet of things unit
Figure 21720DEST_PATH_IMAGE002
The computing node in (1) starts to receive the Internet of things unit
Figure 886908DEST_PATH_IMAGE002
The original power data generated by all common nodes in the system, the time period to be timed
Figure 229028DEST_PATH_IMAGE001
After the completion, the received original electric power data are integrated together to form an internet of things unit
Figure 78035DEST_PATH_IMAGE002
At timed time periods
Figure 655647DEST_PATH_IMAGE001
Raw power data set within
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。
In the big data analysis method of the power internet of things, preferably, the computing node receives the internet of things unit to which the computing node belongs
Figure 419520DEST_PATH_IMAGE002
At timed time periods
Figure 490245DEST_PATH_IMAGE001
Raw power data set of
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According to the original electricityForce data set
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And a timed period
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Internet of things unit
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The influence weight of the common node on the characteristic power data is calculated to obtain the Internet of things unit
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At timed time periods
Figure 35813DEST_PATH_IMAGE001
Characteristic power data of the inside
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。
The big data analysis method of the power internet of things is preferably characterized in that the computing nodes are based on the internet of things unit
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In the timing period of the common node
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Working full load rate and things-internet unit
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The type weight of the common node in (1) is calculated to obtain a timing time period
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Internet of things unit
Figure 421980DEST_PATH_IMAGE002
The influence weight of the normal node in (1) on the characteristic power data.
Electric power object as described aboveThe method for analyzing the networked big data comprises the following steps that preferably, the cloud analyzes a received access request, and a required data identifier is obtained according to an access result required by a user and contained in the access request; the cloud inquires in the storage space of the cloud according to the identification of the required data to obtain characteristic power data
Figure 886460DEST_PATH_IMAGE004
Or raw power data set
Figure 493022DEST_PATH_IMAGE003
According to characteristic power data
Figure 17544DEST_PATH_IMAGE004
Or raw power data set
Figure 771873DEST_PATH_IMAGE003
And analyzing to obtain an access result.
A big data analysis system of an electric power Internet of things comprises the electric power Internet of things and a cloud; wherein, the electric power thing networking includes: the system comprises a plurality of Internet of things units, a plurality of computer nodes and a plurality of computers, wherein each Internet of things unit comprises a plurality of common nodes and a computing node; all common nodes in the Internet of things unit send the generated original power data to the computing nodes in the Internet of things unit to which the common nodes belong; the computing node computes characteristic power data of the Internet of things unit to which the computing node belongs according to the received original power data; the computing node stores the obtained characteristic power data and original power data of the Internet of things unit to the cloud as a storage unit; the cloud receives an access request of a user, obtains characteristic power data or original power data according to the access request, and analyzes the characteristic power data or the original power data to obtain an access result; and the cloud end returns the access result to the user as the response of the access request.
The big data analysis system of the power internet of things as described above, wherein it is preferable that the time period is timed
Figure 836781DEST_PATH_IMAGE001
After starting, the material isLinkage unit
Figure 625746DEST_PATH_IMAGE002
The computing node in (1) starts to receive the Internet of things unit
Figure 258852DEST_PATH_IMAGE002
The original power data generated by all common nodes in the network, the time period to be timed
Figure 500478DEST_PATH_IMAGE001
After the completion, the received original electric power data are integrated together to form an internet of things unit
Figure 41181DEST_PATH_IMAGE002
At timed time periods
Figure 12548DEST_PATH_IMAGE001
Raw power data set in
Figure 613293DEST_PATH_IMAGE003
。
In the big data analysis system of the power internet of things, preferably, the computing node receives the internet of things unit to which the computing node belongs
Figure 545477DEST_PATH_IMAGE002
At timed time periods
Figure 889871DEST_PATH_IMAGE001
Raw power data set of
Figure 715744DEST_PATH_IMAGE003
From raw power data sets
Figure 221812DEST_PATH_IMAGE003
And a timed period
Figure 703609DEST_PATH_IMAGE001
Internet of things unit
Figure 789377DEST_PATH_IMAGE002
The influence weight of the common node on the characteristic power data is calculated to obtain the Internet of things unit
Figure 407440DEST_PATH_IMAGE002
At timed time periods
Figure 349988DEST_PATH_IMAGE001
Characteristic power data of the inside
Figure 115819DEST_PATH_IMAGE004
。
The big data analysis system of the power internet of things as described above, wherein preferably, the computing nodes are based on the internet of things unit
Figure 802015DEST_PATH_IMAGE002
In the timing period of the common node
Figure 477847DEST_PATH_IMAGE001
Working full load rate and things-internet unit
Figure 591297DEST_PATH_IMAGE002
The type weight of the common node in (1) is calculated to obtain a timing time period
Figure 844423DEST_PATH_IMAGE001
Internet of things unit
Figure 68731DEST_PATH_IMAGE002
The influence weight of the normal node in (1) on the characteristic power data.
The big data analysis system of the power internet of things, preferably, the cloud analyzes the received access request, and obtains the identifier of the required data according to the access result required by the user and included in the access request; the cloud inquires in the storage space of the cloud according to the identification of the required data to obtain characteristic power data
Figure 661387DEST_PATH_IMAGE004
Or raw power data set
Figure 149000DEST_PATH_IMAGE003
According to characteristic power data
Figure 827106DEST_PATH_IMAGE004
Or raw power data set
Figure 589525DEST_PATH_IMAGE003
And analyzing to obtain an access result.
Compared with the background art, the big data analysis method and system of the power internet of things can quickly query and analyze the power data stored in the cloud end, and performance of the cloud end is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained by those skilled in the art according to these drawings.
Fig. 1 is a flowchart of a big data analysis method of an electric power internet of things provided in an embodiment of the present application;
fig. 2 is a schematic diagram of a big data analysis system of an electric power internet of things provided in the embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative only and should not be construed as limiting the invention.
Example one
Referring to fig. 1, fig. 1 is a flowchart of a big data analysis method of an electric power internet of things according to an embodiment of the present application.
The application provides a big data analysis method of an electric power Internet of things, which comprises the following steps:
step S110, all common nodes in the Internet of things unit send the generated original power data to the computing nodes in the Internet of things unit to which the common nodes belong;
the power internet of things has a plurality of different power systems, for example: a plurality of production regulation and operation systems, a plurality of marketing and operation service systems and the like. Each power system has different power devices, such as: each production regulation and control and operation system is provided with an online sensor, a networked measuring device and the like, and each marketing and operation service system is provided with power consumption data acquisition equipment, EV charging operation equipment and the like.
In the application, each power system is taken as an internet of things unit, each power device in the internet of things unit (i.e. the power system) is taken as a common node of the internet of things unit, and each common node constantly generates power data (for example, power data collected by a sensor, power data collected by a power data collecting device, and the like). The unified analysis of electric power data is carried out as the unit to use the thing to ally oneself with the unit in this application to and the storage in the high in the clouds.
Each thing allies oneself with all to add in the unit and calculate the node, and all ordinary nodes in the unit are all correlated with all ordinary nodes in this thing allies oneself with the unit in the thing, and all ordinary nodes in this thing allies oneself with the unit and produce the original electric power data after producing the original electric power data, all send the calculation node correlated with it with the original electric power data that produce.
In particular, during a timed period
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After starting, the Internet of things unit
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The computing node in (1) starts to receive the Internet of things unit
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Original generated by all common nodes inElectric data, time period to be timed
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After the completion, the received original electric power data are integrated together to form an internet of things unit
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At timed time periods
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Raw power data set within
Figure 397447DEST_PATH_IMAGE005
Wherein, in the step (A),
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for timing time periods
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Internet of things unit
Figure 923741DEST_PATH_IMAGE002
The 1 st power data generated by the 1 st general node (power device) in (1),
Figure 860473DEST_PATH_IMAGE007
for timing time periods
Figure 33965DEST_PATH_IMAGE001
Internet of things unit
Figure 310226DEST_PATH_IMAGE002
1 st common node of (1)
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The data of the electric power is stored in a memory,
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for timing time periods
Figure 289180DEST_PATH_IMAGE001
Internet of things unit
Figure 747843DEST_PATH_IMAGE002
The amount of power data generated by the 1 st general node in (b),
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for timing time periods
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Internet of things unit
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To (1)
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The 1 st power data generated by one common node,
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for timing time periods
Figure 436934DEST_PATH_IMAGE001
Internet of things unit
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To
Figure 533383DEST_PATH_IMAGE010
Generation of a common node
Figure 279622DEST_PATH_IMAGE012
The data of the electric power is stored in a memory,
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for timing time periods
Figure 757057DEST_PATH_IMAGE001
Internet of things unit
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To (1)
Figure 571746DEST_PATH_IMAGE010
The amount of power data generated by the individual general nodes,
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for timing time periods
Figure 277851DEST_PATH_IMAGE001
Internet of things unit
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To (1)
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The 1 st power data generated by one common node,
Figure 978457DEST_PATH_IMAGE015
for timing time periods
Figure 911778DEST_PATH_IMAGE001
Internet of things unit
Figure 846236DEST_PATH_IMAGE002
To (1)
Figure 433075DEST_PATH_IMAGE014
Generation of a common node
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The data of the electric power is stored in a memory,
Figure 393258DEST_PATH_IMAGE016
for timing time periods
Figure 916643DEST_PATH_IMAGE001
Internet of things unit
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To (1)
Figure 916009DEST_PATH_IMAGE014
The amount of power data generated by the individual general nodes,
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is an internet of things unit
Figure 100183DEST_PATH_IMAGE002
The number of common nodes in (1).
Time period to be timed
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Immediately after the end, entering a timing period
Figure 633112DEST_PATH_IMAGE017
Internet of things unit
Figure 305402DEST_PATH_IMAGE002
The computing node in (1) receives a timing period
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Internet of things unit
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All the common nodes in the system generate original power data, and the received original power data are integrated together to form an internet of things unit
Figure 994506DEST_PATH_IMAGE002
At timed time periods
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Raw power data set of
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。
Step S120, calculating by the computing node according to the received original power data to obtain characteristic power data of the Internet of things unit to which the computing node belongs;
specifically, the computing node receives the internet of things unit to which the computing node belongs
Figure 499940DEST_PATH_IMAGE002
At timed time periods
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Raw power data set of
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By the formula
Figure 565482DEST_PATH_IMAGE020
Calculating to obtain an internet of things unit
Figure 678932DEST_PATH_IMAGE002
At timed time periods
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Characteristic power data of the inside
Figure 421946DEST_PATH_IMAGE021
，
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Is an internet of things unit
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At the timing period of the 1 st ordinary node in
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Internal pair of things unit
Figure 5057DEST_PATH_IMAGE002
The influence weight of the characteristic power data of (a),
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is an internet of things unit
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To (1)
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A common node in the timing period
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Internal pair things unit
Figure 206231DEST_PATH_IMAGE002
The influence weight of the characteristic power data of (a),
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is an internet of things unit
Figure 219503DEST_PATH_IMAGE002
To (1)
Figure 792567DEST_PATH_IMAGE026
A common node in the timing period
Figure 214321DEST_PATH_IMAGE001
Internal pair of things unit
Figure 339272DEST_PATH_IMAGE002
The influence weight of the characteristic power data of (1).
On the basis of the above, the internet of things unit
Figure 948108DEST_PATH_IMAGE002
Each common node in (1) may have different influence on the characteristic power data in different timing time periods, so that the computing node also needs to calculate the timing time period
Figure 121600DEST_PATH_IMAGE001
The internet of things unit is arranged inside
Figure 335544DEST_PATH_IMAGE002
The weight of the influence of all the common nodes in (1) on the characteristic power data.
In particular, by the formula
Figure 569079DEST_PATH_IMAGE027
Calculating to obtain an internet of things unit
Figure 993107DEST_PATH_IMAGE002
To (1)
Figure 704711DEST_PATH_IMAGE024
A common node in the timing period
Figure 101057DEST_PATH_IMAGE001
Internal pair of things unit
Figure 443177DEST_PATH_IMAGE002
Characteristic power data of
Figure 26605DEST_PATH_IMAGE028
Wherein, in the step (A),
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is an internet of things unit
Figure 855070DEST_PATH_IMAGE002
To (1)
Figure 23883DEST_PATH_IMAGE024
A common node in the timing period
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For example: the efficiency of the operation of the electrical equipment,
Figure 538227DEST_PATH_IMAGE030
is an internet of things unit
Figure 846848DEST_PATH_IMAGE002
To (1)
Figure 920984DEST_PATH_IMAGE024
The type weight of each common node, for example: on-line sensingThe type weight of the electric power equipment is preset, and the type weight of the networked measuring device and the type weight of the electricity utilization data acquisition equipment are preset.
Step S130, the computing node stores the obtained characteristic power data and original power data of the Internet of things unit to the cloud as a storage unit;
specifically, the Internet of things unit is obtained at the computing node
Figure 947846DEST_PATH_IMAGE002
At timed time periods
Figure 867260DEST_PATH_IMAGE001
Characteristic power data of the inside
Figure 92705DEST_PATH_IMAGE004
Then, the characteristic power data is used
Figure 947528DEST_PATH_IMAGE004
And raw power data set
Figure 727266DEST_PATH_IMAGE031
And uploading the data to the cloud as a storage unit, and storing the data at the cloud.
Step S140, the cloud receives an access request of a user, obtains characteristic power data or original power data according to the access request, and analyzes the characteristic power data or the original power data to obtain an access result;
and the computing node stores the obtained characteristic power data and the original power data of the Internet of things unit to the cloud as a storage unit.
When a user needs to access data stored in the cloud, the user generates an access request, the access request contains a required access result, and then the generated access request is sent to the cloud.
After receiving an access request of a user, the cloud analyzes the access request, and obtains a required data identifier according to an access result required by the user and contained in the access request, wherein the required data identifier is obtainedMay be characteristic power data
Figure 388054DEST_PATH_IMAGE004
Or raw power data set
Figure 530322DEST_PATH_IMAGE003
. Then, the cloud inquires in the storage space of the cloud according to the identification of the required data to obtain characteristic power data
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Or raw power data set
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Then according to the characteristic power data
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Or raw power data set
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And analyzing to obtain an access result.
And step S150, the cloud end takes the access result as a response of the access request and returns the access result to the user.
And after the cloud end analyzes and obtains the access result, the access result is used as the response of the access request and returned to the user.
Example two
Referring to fig. 2, fig. 2 is a schematic view of a big data analysis system of an electric power internet of things according to an embodiment of the present application.
The application provides a big data analysis system of an electric power Internet of things, which comprises an electric power Internet of things 210 and a cloud 220; wherein, electric power thing networking 210 includes: the system comprises a plurality of internet of things units 211, wherein each internet of things unit 211 comprises a plurality of common nodes 2111 and a computing node 2112.
All the common nodes 2111 in the internet of things unit 211 transmit the generated raw power data to the computing nodes 2112 in the internet of things unit 211 to which they belong.
The power internet of things 210 has a plurality of different power systems, for example: a plurality of production regulation and operation systems, a plurality of marketing and operation service systems and the like. Each power system has different power devices, such as: each production regulation and control and operation system is provided with an online sensor, a networked measuring device and the like, and each marketing and operation service system is provided with power consumption data acquisition equipment, EV charging operation equipment and the like.
In the present application, each power system is taken as an internet of things unit 211, each power device in the internet of things unit 211 (i.e., the power system) is taken as a common node 2111 of the internet of things unit 211, and each common node 2111 continuously generates power data (e.g., power data collected by a sensor, power data collected by a power data collecting device, etc.). The unified analysis of electric power data is carried out with thing allies oneself with unit 211 as the unit in this application to and the storage in high in the clouds 220.
Each of the internet of things units 211 is additionally provided with a calculation node 2112, the calculation node 2112 in the internet of things unit 211 is associated with all the common nodes 2111 in the internet of things unit 211, and after the raw power data is generated, all the common nodes 2111 in the internet of things unit 211 transmit the generated raw power data to the calculation node 2112 associated therewith.
In particular, during a timed period
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After starting, the Internet of things unit
Figure 563186DEST_PATH_IMAGE002
The computing node in (1) starts to receive the Internet of things unit
Figure 565778DEST_PATH_IMAGE002
The original power data generated by all common nodes in the system, the time period to be timed
Figure 292425DEST_PATH_IMAGE001
After the completion, the received original electric power data are integrated together to form an internet of things unit
Figure 722269DEST_PATH_IMAGE002
At timed time periods
Figure 291791DEST_PATH_IMAGE001
Raw power data set in
Figure 832494DEST_PATH_IMAGE032
Wherein, in the step (A),
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for timing time periods
Figure 279973DEST_PATH_IMAGE001
Internet of things unit
Figure 8894DEST_PATH_IMAGE002
The 1 st power data generated by the 1 st general node (power device) in (1),
Figure 681184DEST_PATH_IMAGE034
for timing time periods
Figure 913582DEST_PATH_IMAGE001
Internet of things unit
Figure 950808DEST_PATH_IMAGE002
1 st common node of (1)
Figure 104709DEST_PATH_IMAGE035
The data of the electric power is stored in a memory,
Figure 252794DEST_PATH_IMAGE035
for timing time periods
Figure 605278DEST_PATH_IMAGE001
Internet of things unit
Figure 875722DEST_PATH_IMAGE002
The amount of power data generated by the 1 st general node in (b),
Figure 579236DEST_PATH_IMAGE036
for timing time periods
Figure 468694DEST_PATH_IMAGE001
Internet of things unit
Figure 675685DEST_PATH_IMAGE002
To (1)
Figure 54714DEST_PATH_IMAGE037
The 1 st power data generated by one common node,
Figure 307840DEST_PATH_IMAGE038
for timing time periods
Figure 797728DEST_PATH_IMAGE001
Internet of things unit
Figure 328066DEST_PATH_IMAGE002
To (1)
Figure 346838DEST_PATH_IMAGE037
Generation of a common node
Figure 24944DEST_PATH_IMAGE012
The data of the electric power is stored in a memory,
Figure 380839DEST_PATH_IMAGE012
for timing time periods
Figure 828000DEST_PATH_IMAGE001
Internal things connection unit
Figure 283253DEST_PATH_IMAGE002
To (1)
Figure 120759DEST_PATH_IMAGE037
The amount of power data generated by the individual general nodes,
Figure 952448DEST_PATH_IMAGE039
for timing time periods
Figure 582013DEST_PATH_IMAGE001
Internet of things unit
Figure 208166DEST_PATH_IMAGE002
To (1)
Figure 595285DEST_PATH_IMAGE040
The 1 st power data generated by one common node,
Figure 168349DEST_PATH_IMAGE041
for timing time periods
Figure 590103DEST_PATH_IMAGE001
Internet of things unit
Figure 715054DEST_PATH_IMAGE002
To (1)
Figure 323890DEST_PATH_IMAGE040
Generation of a common node
Figure 497382DEST_PATH_IMAGE042
The data of the electric power is stored in a memory,
Figure 711326DEST_PATH_IMAGE042
for timing time periods
Figure 944861DEST_PATH_IMAGE001
Internet of things unit
Figure 40993DEST_PATH_IMAGE002
To (1)
Figure 80493DEST_PATH_IMAGE040
The amount of power data generated by the individual general nodes,
Figure 211260DEST_PATH_IMAGE040
is an internet of things unit
Figure 553380DEST_PATH_IMAGE002
The number of common nodes in (1).
Time period to be timed
Figure 136808DEST_PATH_IMAGE001
Immediately after the end, entering a timing period
Figure 917682DEST_PATH_IMAGE043
Internet of things unit
Figure 965273DEST_PATH_IMAGE002
The computing node in (1) receives a timing period
Figure 540610DEST_PATH_IMAGE043
Internal things connection unit
Figure 814597DEST_PATH_IMAGE002
All the common nodes in the system generate original power data, and the received original power data are integrated together to form an internet of things unit
Figure 868004DEST_PATH_IMAGE002
At timed time periods
Figure 973363DEST_PATH_IMAGE043
Raw power data set of
Figure 781919DEST_PATH_IMAGE044
。
The calculation node 2112 calculates the characteristic power data of the internet-of-things unit 211 to which it belongs according to the received original power data.
Specifically, the computing node receives the internet of things unit to which the computing node belongs
Figure 605518DEST_PATH_IMAGE002
At timed time periods
Figure 197037DEST_PATH_IMAGE001
Raw power data set of
Figure 94586DEST_PATH_IMAGE045
By the formula
Figure 277305DEST_PATH_IMAGE046
Calculating to obtain an internet of things unit
Figure 384939DEST_PATH_IMAGE002
At timed time periods
Figure 780148DEST_PATH_IMAGE001
Characteristic power data in
Figure 860099DEST_PATH_IMAGE047
，
Figure 885824DEST_PATH_IMAGE048
Is an internet of things unit
Figure 152857DEST_PATH_IMAGE002
At the timing period of the 1 st ordinary node in (1)
Figure 617337DEST_PATH_IMAGE001
Internal pair of things unit
Figure 614112DEST_PATH_IMAGE002
The influence weight of the characteristic power data of (a),
Figure 873055DEST_PATH_IMAGE049
is an internet of things unit
Figure 830646DEST_PATH_IMAGE002
To (1)
Figure 567658DEST_PATH_IMAGE050
A common node in the timing period
Figure 356623DEST_PATH_IMAGE001
Internal pair of things unit
Figure 114363DEST_PATH_IMAGE002
The influence weight of the characteristic power data of (a),
Figure 621568DEST_PATH_IMAGE051
is an internet of things unit
Figure 896691DEST_PATH_IMAGE002
To (1)
Figure 743425DEST_PATH_IMAGE040
A common node in the timing period
Figure 344170DEST_PATH_IMAGE001
Internal pair of things unit
Figure 400988DEST_PATH_IMAGE002
The influence weight of the characteristic power data of (1).
On the basis of the above, the Internet of things unit
Figure 479802DEST_PATH_IMAGE002
Each common node in (1) may have different influence on the characteristic power data in different timing time periods, so that the computing node also needs to calculate the timing time period
Figure 243359DEST_PATH_IMAGE001
The internet of things unit is arranged inside
Figure 218268DEST_PATH_IMAGE002
The influence weight of all the common nodes in (1) on the characteristic power data.
In particular, by the formula
Figure 434486DEST_PATH_IMAGE052
Calculating to obtain an internet of things unit
Figure 644887DEST_PATH_IMAGE002
To (1)
Figure 997371DEST_PATH_IMAGE050
A common node in the timing period
Figure 205499DEST_PATH_IMAGE001
Internal pair things unit
Figure 846696DEST_PATH_IMAGE002
Characteristic power data of
Figure 532892DEST_PATH_IMAGE053
Wherein, in the process,
Figure 5462DEST_PATH_IMAGE054
is an internet of things unit
Figure 446807DEST_PATH_IMAGE002
To (1)
Figure 637617DEST_PATH_IMAGE050
A common node in the timing period
Figure 65187DEST_PATH_IMAGE001
For example: the efficiency of the operation of the electrical equipment,
Figure 126684DEST_PATH_IMAGE055
is an internet of things unit
Figure 676614DEST_PATH_IMAGE002
To
Figure 417037DEST_PATH_IMAGE050
The type weight of each common node, for example: the type weight of the on-line sensor, the type weight of the networked measuring device and the type weight of the electricity utilization data acquisition equipment are preset.
The calculation node 2112 stores the obtained characteristic power data and the original power data of the internet of things unit 211 as a storage unit to the cloud.
Specifically, the Internet of things unit is obtained at the computing node
Figure 710615DEST_PATH_IMAGE002
At timed time periods
Figure 95460DEST_PATH_IMAGE001
Characteristic power data of the inside
Figure 285133DEST_PATH_IMAGE056
Then, the characteristic power data is used
Figure 450535DEST_PATH_IMAGE056
And raw power data set
Figure 344542DEST_PATH_IMAGE057
And uploading the data to the cloud as a storage unit, and storing the data at the cloud.
The cloud 220 receives an access request of a user, obtains characteristic power data or original power data according to the access request query, and analyzes the characteristic power data or the original power data to obtain an access result.
The computing node 2112 stores the obtained characteristic power data and the original power data of the internet of things unit 211 as a storage unit to the cloud 220.
When a user needs to access data stored in the cloud 220, the user generates an access request, the access request includes a required access result, and then the generated access request is sent to the cloud 220.
After receiving the access request of the user, the cloud 220 parses the access request, and obtains an identifier of required data according to an access result required by the user and included in the access request, where the required data may be characteristic power data
Figure 911790DEST_PATH_IMAGE056
Or raw power data set
Figure 272364DEST_PATH_IMAGE003
. Then, the cloud 220 queries in the storage space of the cloud according to the identifier of the required data to obtain the characteristic power data
Figure 862745DEST_PATH_IMAGE056
Or raw power data set
Figure 498126DEST_PATH_IMAGE003
Then according to the characteristic power data
Figure 716618DEST_PATH_IMAGE056
Or raw power data set
Figure 513672DEST_PATH_IMAGE003
And analyzing to obtain an access result.
The cloud 220 returns the access result to the user as a response to the access request.
After the cloud 220 analyzes and obtains the access result, the access result is used as a response of the access request and returned to the user.
According to the method and the device, the original power data set and the corresponding characteristic power data are stored in the cloud, the data volume of the characteristic power data is far less than that of the original power data set, and the quantity of the characteristic power data is smaller than that of the original power data set, so that the requirement can be met when a user obtains the characteristic power data, or the required access result of the user can be obtained according to the characteristic power data, the characteristic power data only need to be inquired and analyzed, the characteristic power data are inquired and analyzed, the method and the device are quicker when the characteristic power data are inquired and analyzed compared with the original power data, and therefore the performance of the cloud is improved.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.

Claims (10)

1. A big data analysis method of an electric power Internet of things is characterized by comprising the following steps:
step S110, all common nodes in the Internet of things unit send the generated original power data to the computing nodes in the Internet of things unit to which the common nodes belong;
step S120, calculating to obtain characteristic power data of an Internet of things unit to which the computing node belongs according to the received original power data by the computing node;
step S130, the computing node stores the obtained characteristic power data and original power data of the Internet of things unit to the cloud as a storage unit;
step S140, the cloud receives an access request of a user, obtains characteristic power data or original power data according to the access request, and analyzes the characteristic power data or the original power data to obtain an access result;
and step S150, the cloud end takes the access result as a response of the access request and returns the access result to the user.
2. The big data analysis method of the power internet of things as claimed in claim 1, wherein the big data analysis method is performed in a timing period
Figure 271816DEST_PATH_IMAGE001
Start ofRear, thing connection unit
Figure 392219DEST_PATH_IMAGE002
The computing node in (1) starts to receive the Internet of things unit
Figure 437536DEST_PATH_IMAGE002
The original power data generated by all common nodes in the network, the time period to be timed
Figure 160641DEST_PATH_IMAGE001
After the completion, the received original electric power data are integrated together to form an internet of things unit
Figure 975013DEST_PATH_IMAGE002
At timed time periods
Figure 63055DEST_PATH_IMAGE001
Raw power data set in
Figure 533351DEST_PATH_IMAGE003
。
3. The big data analysis method for the power internet of things as claimed in claim 2, wherein the computing node receives the internet of things unit to which the computing node belongs
Figure 997830DEST_PATH_IMAGE002
At timed time periods
Figure 666709DEST_PATH_IMAGE001
Raw power data set of
Figure 987969DEST_PATH_IMAGE003
From raw power data sets
Figure 7877DEST_PATH_IMAGE003
And a timed period
Figure 948151DEST_PATH_IMAGE001
Internet of things unit
Figure 737116DEST_PATH_IMAGE002
The influence weight of the common node on the characteristic power data is calculated to obtain the Internet of things unit
Figure 494856DEST_PATH_IMAGE002
At timed time periods
Figure 736482DEST_PATH_IMAGE001
Characteristic power data in
Figure 277184DEST_PATH_IMAGE004
。
4. The big data analysis method of the power internet of things as claimed in claim 3, wherein the computing nodes are based on the internet of things unit
Figure 123918DEST_PATH_IMAGE002
In the timing period of the common node
Figure 724663DEST_PATH_IMAGE001
Working full load rate and things-internet unit
Figure 781481DEST_PATH_IMAGE002
The type weight of the common node in (1) is calculated to obtain a timing time period
Figure 125875DEST_PATH_IMAGE001
Internet of things unit
Figure 623852DEST_PATH_IMAGE002
The influence weight of the normal node in (1) on the characteristic power data.
5. The big data analysis method of the power internet of things as claimed in any one of claims 1 to 4, wherein the cloud analyzes the received access request, and obtains the identifier of the required data according to the access result required by the user and contained in the access request;
the cloud inquires in the storage space of the cloud according to the identification of the required data to obtain characteristic power data
Figure 598761DEST_PATH_IMAGE005
Or raw power data set
Figure 814979DEST_PATH_IMAGE006
According to characteristic power data
Figure 25381DEST_PATH_IMAGE005
Or raw power data set
Figure 377865DEST_PATH_IMAGE006
And analyzing to obtain an access result.
6. A big data analysis system of an electric power Internet of things is characterized by comprising an electric power Internet of things and a cloud end; wherein, the electric power thing networking includes: the system comprises a plurality of Internet of things units, a plurality of computer units and a plurality of computers, wherein each Internet of things unit comprises a plurality of common nodes and a computing node;
all common nodes in the Internet of things unit send the generated original power data to the computing nodes in the Internet of things unit to which the common nodes belong; the computing node computes characteristic power data of the Internet of things unit to which the computing node belongs according to the received original power data; the computing node stores the obtained characteristic power data and the original power data of the Internet of things unit as a storage unit to a cloud; the cloud receives an access request of a user, obtains characteristic power data or original power data according to the access request, and analyzes the characteristic power data or the original power data to obtain an access result; and the cloud end returns the access result to the user as the response of the access request.
7. The big data analysis system of the power internet of things as claimed in claim 6, wherein the big data analysis system is used for timing time period
Figure 585992DEST_PATH_IMAGE001
After the start, the Internet of things unit
Figure 227189DEST_PATH_IMAGE002
The computing node in (1) starts to receive the Internet of things unit
Figure 913385DEST_PATH_IMAGE002
The original power data generated by all common nodes in the network, the time period to be timed
Figure 713851DEST_PATH_IMAGE001
After finishing, the received original electric power data are integrated together to form an internet of things unit
Figure 827300DEST_PATH_IMAGE002
At timed time periods
Figure 18110DEST_PATH_IMAGE001
Raw power data set in
Figure 445681DEST_PATH_IMAGE007
。
8. The big data analysis system of the power internet of things as claimed in claim 7, wherein the computing node receives the internet of things unit to which the computing node belongs
Figure 772757DEST_PATH_IMAGE002
At timed time periods
Figure 57108DEST_PATH_IMAGE001
Raw power data set of
Figure 797530DEST_PATH_IMAGE007
From raw power data sets
Figure 91109DEST_PATH_IMAGE007
And a timed period
Figure 475954DEST_PATH_IMAGE001
Internal things connection unit
Figure 665626DEST_PATH_IMAGE002
The influence weight of the common node on the characteristic power data is calculated to obtain the Internet of things unit
Figure 831029DEST_PATH_IMAGE002
At timed time periods
Figure 725035DEST_PATH_IMAGE001
Characteristic power data of the inside
Figure 292283DEST_PATH_IMAGE008
。
9. The big data analysis system of the power internet of things as claimed in claim 8, wherein the computing nodes are based on the internet of things unit
Figure 856119DEST_PATH_IMAGE002
In the timing period
Figure 243238DEST_PATH_IMAGE001
Working full load rate and things-internet unit
Figure 878619DEST_PATH_IMAGE002
The type weight of the common node in (1) is calculated to obtain a timing time period
Figure 97111DEST_PATH_IMAGE001
Internet of things unit
Figure 159745DEST_PATH_IMAGE002
The influence weight of the normal node in (1) on the characteristic power data.
10. The big data analysis system of the power internet of things as claimed in any one of claims 6 to 9, wherein the cloud analyzes the received access request, and obtains the identifier of the required data according to the access result required by the user and contained in the access request;
the cloud inquires in the storage space of the cloud according to the identification of the required data to obtain characteristic power data
Figure 768580DEST_PATH_IMAGE008
Or raw power data set
Figure 145335DEST_PATH_IMAGE009
According to characteristic electric power data
Figure 421596DEST_PATH_IMAGE008
Or raw power data set
Figure 717448DEST_PATH_IMAGE009
And analyzing to obtain an access result.
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